High-resolution 3D models of Caulobacter crescentus chromosome reveal genome structural variability and organization

Elucidation of Spatial Positioning of Ribosomes around Chromosome in Escherichia coli Cytoplasm via a Data-Informed Polymer-Based Model

The spatial arrangement of ribosomes and chromosome in Escherichia coli's cytoplasm challenges conventional wisdom. Contrary to the notion of ribosomes acting as inert crowders to the chromosome in the cytoplasm, here we propose a nuanced view by integrating a wide array of experimental data sets into a polymer-based computer model. A set of data-informed computer simulations determines that a delicate balance of attractive and repulsive interactions between ribosomes and the chromosome is required in order to reproduce experimentally obtained linear densities and brings forth the view that ribosomes are not mere inert crowders in the cytoplasm. The model finds that the ribosomes represent themselves as a poor solvent for the chromosome with a 50 nm mesh size, consistent with previous experimental analysis. Our multidimensional analysis of ribosome distribution, both free (30S and 50S) and bound (70S polysome), uncovers a relatively less pronounced segregation pattern than previously thought. Notably, we identify a ribosome-rich central region within the innermost core of the nucleoid. Moreover, our exploration of the chromosome mesh size and the conformation of bound ribosomes suggests that these ribosomes maintain elongated shapes, enabling them to navigate through the chromosome mesh and access the central core. This dynamic localization challenges the static segregation model and underscores the pivotal role of ribosome-chromosome interactions in cellular media.

Physical models of bacterial chromosomes

The interplay between bacterial chromosome organization and functions such as transcription and replication can be studied in increasing detail using novel experimental techniques. Interpreting the resulting quantitative data, however, can be theoretically challenging. In this minireview, we discuss how connecting experimental observations to biophysical theory and modeling can give rise to new insights on bacterial chromosome organization. We consider three flavors of models of increasing complexity: simple polymer models that explore how physical constraints, such as confinement or plectoneme branching, can affect bacterial chromosome organization; bottom-up mechanistic models that connect these constraints to their underlying causes, for instance, chromosome compaction to macromolecular crowding, or supercoiling to transcription; and finally, data-driven methods for inferring interpretable and quantitative models directly from complex experimental data. Using recent examples, we discuss how biophysical models can both deepen our understanding of how bacterial chromosomes are structured and give rise to novel predictions about bacterial chromosome organization.

Computational methods for analysing multiscale 3D genome organization

Recent progress in whole-genome mapping and imaging technologies has enabled the characterization of the spatial organization and folding of the genome in the nucleus. In parallel, advanced computational methods have been developed to leverage these mapping data to reveal multiscale three-dimensional (3D) genome features and to provide a more complete view of genome structure and its connections to genome functions such as transcription. Here, we discuss how recently developed computational tools, including machine-learning-based methods and integrative structure-modelling frameworks, have led to a systematic, multiscale delineation of the connections among different scales of 3D genome organization, genomic and epigenomic features, functional nuclear components and genome function. However, approaches that more comprehensively integrate a wide variety of genomic and imaging datasets are still needed to uncover the functional role of 3D genome structure in defining cellular phenotypes in health and disease.

Explicit ion modeling predicts physicochemical interactions for chromatin organization

Molecular mechanisms that dictate chromatin organization in vivo are under active investigation, and the extent to which intrinsic interactions contribute to this process remains debatable. A central quantity for evaluating their contribution is the strength of nucleosome-nucleosome binding, which previous experiments have estimated to range from 2 to 14 kBT. We introduce an explicit ion model to dramatically enhance the accuracy of residue-level coarse-grained modeling approaches across a wide range of ionic concentrations. This model allows for de novo predictions of chromatin organization and remains computationally efficient, enabling large-scale conformational sampling for free energy calculations. It reproduces the energetics of protein-DNA binding and unwinding of single nucleosomal DNA, and resolves the differential impact of mono- and divalent ions on chromatin conformations. Moreover, we showed that the model can reconcile various experiments on quantifying nucleosomal interactions, providing an explanation for the large discrepancy between existing estimations. We predict the interaction strength at physiological conditions to be 9 kBT, a value that is nonetheless sensitive to DNA linker length and the presence of linker histones. Our study strongly supports the contribution of physicochemical interactions to the phase behavior of chromatin aggregates and chromatin organization inside the nucleus.

Chromosome structure modeling tools and their evaluation in bacteria

The three-dimensional (3D) structure of bacterial chromosomes is crucial for understanding chromosome function. With the growing availability of high-throughput chromosome conformation capture (3C/Hi-C) data, the 3D structure reconstruction algorithms have become powerful tools to study bacterial chromosome structure and function. It is highly desired to have a recommendation on the chromosome structure reconstruction tools to facilitate the prokaryotic 3D genomics. In this work, we review existing chromosome 3D structure reconstruction algorithms and classify them based on their underlying computational models into two categories: constraint-based modeling and thermodynamics-based modeling. We briefly compare these algorithms utilizing 3C/Hi-C datasets and fluorescence microscopy data obtained from Escherichia coli and Caulobacter crescentus, as well as simulated datasets. We discuss current challenges in the 3D reconstruction algorithms for bacterial chromosomes, primarily focusing on software usability. Finally, we briefly prospect future research directions for bacterial chromosome structure reconstruction algorithms.

Shedding Light on Bacterial Chromosome Structure: Exploring the Significance of 3C-Based Approaches

The complex architecture of DNA within living organisms is essential for maintaining the genetic information that dictates their functions and characteristics. Among the many complexities of genetic material organization, the folding and arrangement of DNA into chromosomes play a critical role in regulating gene expression, replication, and other essential cellular processes. Bacteria, despite their apparently simple cellular structure, exhibit a remarkable level of chromosomal organization that influences their adaptability and survival in diverse environments. Understanding the three-dimensional arrangement of bacterial chromosomes has long been a challenge due to technical limitations, but the development of Chromosome Conformation Capture (3C) methods revolutionized our ability to explore the hierarchical structure and the dynamics of bacterial genomes. Here, we review the major advances in the field of bacterial chromosome structure using 3C technology over the past decade.

Integrative modeling of JCVI-Syn3A nucleoids with a modular approach

A lattice-based method is presented for creating 3D models of entire bacterial nucleoids integrating ultrastructural information cryoelectron tomography, genomic and proteomic data, and experimental atomic structures of biomolecules and assemblies. The method is used to generate models of the minimal genome bacterium JCVI-Syn3A, producing a series of models that test hypotheses about transcription, condensation, and overall distribution of the genome. Lattice models are also used to generate atomic models of an entire JCVI-Syn3A cell.

Explicit Ion Modeling Predicts Physicochemical Interactions for Chromatin Organization

Molecular mechanisms that dictate chromatin organization in vivo are under active investigation, and the extent to which intrinsic interactions contribute to this process remains debatable. A central quantity for evaluating their contribution is the strength of nucleosome-nucleosome binding, which previous experiments have estimated to range from 2 to 14 kBT. We introduce an explicit ion model to dramatically enhance the accuracy of residue-level coarse-grained modeling approaches across a wide range of ionic concentrations. This model allows for de novo predictions of chromatin organization and remains computationally efficient, enabling large-scale conformational sampling for free energy calculations. It reproduces the energetics of protein-DNA binding and unwinding of single nucleosomal DNA, and resolves the differential impact of mono and divalent ions on chromatin conformations. Moreover, we showed that the model can reconcile various experiments on quantifying nucleosomal interactions, providing an explanation for the large discrepancy between existing estimations. We predict the interaction strength at physiological conditions to be 9 kBT, a value that is nonetheless sensitive to DNA linker length and the presence of linker histones. Our study strongly supports the contribution of physicochemical interactions to the phase behavior of chromatin aggregates and chromatin organization inside the nucleus.

The landscape of the histone-organized chromatin of Bdellovibrionota bacteria

Histone proteins have traditionally been thought to be restricted to eukaryotes and most archaea, with eukaryotic nucleosomal histones deriving from their archaeal ancestors. In contrast, bacteria lack histones as a rule. However, histone proteins have recently been identified in a few bacterial clades, most notably the phylum Bdellovibrionota, and these histones have been proposed to exhibit a range of divergent features compared to histones in archaea and eukaryotes. However, no functional genomic studies of the properties of Bdellovibrionota chromatin have been carried out. In this work, we map the landscape of chromatin accessibility, active transcription and three-dimensional genome organization in a member of Bdellovibrionota (a Bacteriovorax strain). We find that, similar to what is observed in some archaea and in eukaryotes with compact genomes such as yeast, Bacteriovorax chromatin is characterized by preferential accessibility around promoter regions. Similar to eukaryotes, chromatin accessibility in Bacteriovorax positively correlates with gene expression. Mapping active transcription through single-strand DNA (ssDNA) profiling revealed that unlike in yeast, but similar to the state of mammalian and fly promoters, Bacteriovorax promoters exhibit very strong polymerase pausing. Finally, similar to that of other bacteria without histones, the Bacteriovorax genome exists in a three-dimensional (3D) configuration organized by the parABS system along the axis defined by replication origin and termination regions. These results provide a foundation for understanding the chromatin biology of the unique Bdellovibrionota bacteria and the functional diversity in chromatin organization across the tree of life.

Evaluating the role of the nuclear microenvironment in gene function by population-based modeling

The nuclear folding of chromosomes relative to nuclear bodies is an integral part of gene function. Here, we demonstrate that population-based modeling-from ensemble Hi-C data-provides a detailed description of the nuclear microenvironment of genes and its role in gene function. We define the microenvironment by the subnuclear positions of genomic regions with respect to nuclear bodies, local chromatin compaction, and preferences in chromatin compartmentalization. These structural descriptors are determined in single-cell models, thereby revealing the structural variability between cells. We demonstrate that the microenvironment of a genomic region is linked to its functional potential in gene transcription, replication, and chromatin compartmentalization. Some chromatin regions feature a strong preference for a single microenvironment, due to association with specific nuclear bodies in most cells. Other chromatin shows high structural variability, which is a strong indicator of functional heterogeneity. Moreover, we identify specialized nuclear microenvironments, which distinguish chromatin in different functional states and reveal a key role of nuclear speckles in chromosome organization. We demonstrate that our method produces highly predictive three-dimensional genome structures, which accurately reproduce data from a variety of orthogonal experiments, thus considerably expanding the range of Hi-C data analysis.

Interpretation of organizational role of proteins on E. coli nucleoid via Hi-C integrated model

Several proteins in Escherichia coli work together to maintain the complex organization of its chromosome. However, the individual roles of these so-called nucleoid-associated proteins (NAPs) in chromosome architectures are not well characterized. Here, we quantitatively dissect the organizational roles of Heat Unstable (HU), a ubiquitous protein in E. coli and MatP, an NAP specifically binding to the Ter macrodomain of the chromosome. Toward this end, we employ a polymer physics-based computer model of wild-type chromosome and their HU- and MatP-devoid counterparts by incorporating their respective experimentally derived Hi-C contact matrix, cell dimensions, and replication status of the chromosome commensurate with corresponding growth conditions. Specifically, our model for the HU-devoid chromosome corroborates well with the microscopy observation of compaction of chromosome at short genomic range but diminished long-range interactions, justifying precedent hypothesis of segregation defect upon HU removal. Control simulations point out that the change in cell dimension and chromosome content in the process of HU removal holds the key to the observed differences in chromosome architecture between wild-type and HU-devoid cells. On the other hand, simulation of MatP-devoid chromosome led to locally enhanced contacts between Ter and its flanking macrodomains, consistent with previous recombination assay experiments and MatP's role in insulation of the Ter macrodomain from the rest of the chromosome. However, the simulation indicated no change in matS sites' localization. Rather, a set of designed control simulations showed that insulation of Ter is not caused by bridging of distant matS sites, also lending credence to a recent mobility experiment on various loci of the E. coli chromosome. Together, the investigations highlight the ability of an integrative model of the bacterial genome in elucidating the role of NAPs and in reconciling multiple experimental observations.

Mesoscience in cell biology and cancer research

Mesoscale characteristics and their interdimensional correlation are the focus of contemporary interdisciplinary research. Mesoscience is a discipline that has the potential to radically update the existing knowledge structure, which differs from the conventional unit-scale and system-scale research models, revealing a previously untouchable area for scientific research. Integrative biology research aims to dissect the complex problems of life systems by conducting comprehensive research and integrating various disciplines from all biological levels of the living organism. However, the mesoscientific issues between different research units are neglected and challenging. Mesoscale research in biology requires the integration of research theories and methods from other disciplines (mathematics, physics, engineering, and even visual imaging) to investigate theoretical and frontier questions of biological processes through experiments, computations, and modeling. We reviewed  integrative paradigms and methods for the biological mesoscale problems (focusing on oncology research) and prospected the potential of their multiple dimensions and upcoming challenges. We expect to establish an interactive and collaborative theoretical platform for further expanding the depth and width of our understanding on the nature of biology.

Uncovering the Principles of Genome Folding by 3D Chromatin Modeling

Our understanding of how genomic DNA is tightly packed inside the nucleus, yet is still accessible for vital cellular processes, has grown dramatically over recent years with advances in microscopy and genomics technologies. Computational methods have played a pivotal role in the structural interpretation of experimental data, which helped unravel some organizational principles of genome folding. Here, we give an overview of current computational efforts in mechanistic and data-driven 3D chromatin structure modeling. We discuss strengths and limitations of different methods and evaluate the added value and benefits of computational approaches to infer the 3D structural and dynamic properties of the genome and its underlying mechanisms at different scales and resolution, ranging from the dynamic formation of chromatin loops and topological associated domains to nuclear compartmentalization of chromatin and nuclear bodies.

Facilitated Dissociation of Nucleoid Associated Proteins from DNA in the Bacterial Confinement

Transcription machinery depends on the temporal formation of protein-DNA complexes. Recent experiments demonstrated that not only the formation but also the lifetime of such complexes can affect the transcriptional machinery. In parallel, in vitro single-molecule studies showed that nucleoid-associated proteins (NAPs) leave the DNA rapidly as the bulk concentration of the protein increases via facilitated dissociation (FD). Nevertheless, whether such a concentration-dependent mechanism is functional in a bacterial cell, in which NAP levels and the 3d chromosomal structure are often coupled, is not clear a priori. Here, by using extensive coarse-grained molecular simulations, we model the unbinding of specific and nonspecific dimeric NAPs from a high-molecular-weight circular DNA molecule in a cylindrical structure mimicking the cellular confinement of a bacterial chromosome. Our simulations confirm that physiologically relevant peak protein levels (tens of micromolar) lead to highly compact chromosomal structures. This compaction results in rapid off rates (shorter DNA residence times) for specifically DNA-binding NAPs, such as the factor for inversion stimulation, which mostly dissociate via a segmental jump mechanism. Contrarily, for nonspecific NAPs, which are more prone to leave their binding sites via 1d sliding, the off rates decrease as the protein levels increase. The simulations with restrained chromosome models reveal that chromosome compaction is in favor of faster dissociation but only for specific proteins, and nonspecific proteins are not affected by the chromosome compaction. Overall, our results suggest that the cellular concentration level of a structural DNA-binding protein can be highly intermingled with its DNA residence time.

Building Structural Models of a Whole Mycoplasma Cell

Building structural models of entire cells has been a long-standing cross-discipline challenge for the research community, as it requires an unprecedented level of integration between multiple sources of biological data and enhanced methods for computational modeling and visualization. Here, we present the first 3D structural models of an entire Mycoplasma genitalium (MG) cell, built using the CellPACK suite of computational modeling tools. Our model recapitulates the data described in recent whole-cell system biology simulations and provides a structural representation for all MG proteins, DNA and RNA molecules, obtained by combining experimental and homology-modeled structures and lattice-based models of the genome. We establish a framework for gathering, curating and evaluating these structures, exposing current weaknesses of modeling methods and the boundaries of MG structural knowledge, and visualization methods to explore functional characteristics of the genome and proteome. We compare two approaches for data gathering, a manually-curated workflow and an automated workflow that uses homologous structures, both of which are appropriate for the analysis of mesoscale properties such as crowding and volume occupancy. Analysis of model quality provides estimates of the regularization that will be required when these models are used as starting points for atomic molecular dynamics simulations.

Integrative approaches in genome structure analysis

New technological advances in integrated imaging, sequencing-based assays, and computational analysis have revolutionized our view of genomes in terms of their structure and dynamics in space and time. These advances promise a deeper understanding of genome functions and mechanistic insights into how the nucleus is spatially organized and functions. These wide arrays of complementary data provide an opportunity to produce quantitative integrative models of nuclear organization. In this article, we highlight recent key developments and discuss the outlook for these fields.

Multiscale modeling of genome organization with maximum entropy optimization

Three-dimensional (3D) organization of the human genome plays an essential role in all DNA-templated processes, including gene transcription, gene regulation, and DNA replication. Computational modeling can be an effective way of building high-resolution genome structures and improving our understanding of these molecular processes. However, it faces significant challenges as the human genome consists of over 6 × 109 base pairs, a system size that exceeds the capacity of traditional modeling approaches. In this perspective, we review the progress that has been made in modeling the human genome. Coarse-grained models parameterized to reproduce experimental data via the maximum entropy optimization algorithm serve as effective means to study genome organization at various length scales. They have provided insight into the principles of whole-genome organization and enabled de novo predictions of chromosome structures from epigenetic modifications. Applications of these models at a near-atomistic resolution further revealed physicochemical interactions that drive the phase separation of disordered proteins and dictate chromatin stability in situ. We conclude with an outlook on the opportunities and challenges in studying chromosome dynamics.

A Hi-C data-integrated model elucidates E. coli chromosome's multiscale organization at various replication stages

The chromosome of Escherichia coli is riddled with multi-faceted complexity. The emergence of chromosome conformation capture techniques are providing newer ways to explore chromosome organization. Here we combine a beads-on-a-spring polymer-based framework with recently reported Hi-C data for E. coli chromosome, in rich growth condition, to develop a comprehensive model of its chromosome at 5 kb resolution. The investigation focuses on a range of diverse chromosome architectures of E. coli at various replication states corresponding to a collection of cells, individually present in different stages of cell cycle. The Hi-C data-integrated model captures the self-organization of E. coli chromosome into multiple macrodomains within a ring-like architecture. The model demonstrates that the position of oriC is dependent on architecture and replication state of chromosomes. The distance profiles extracted from the model reconcile fluorescence microscopy and DNA-recombination assay experiments. Investigations into writhe of the chromosome model reveal that it adopts helix-like conformation with no net chirality, earlier hypothesized in experiments. A genome-wide radius of gyration map captures multiple chromosomal interaction domains and identifies the precise locations of rrn operons in the chromosome. We show that a model devoid of Hi-C encoded information would fail to recapitulate most genomic features unique to E. coli.

Connection Between Chromosomal Location and Function of CtrA Phosphorelay Genes in Alphaproteobacteria

Most bacterial chromosomes are circular, with replication starting at one origin (ori) and proceeding on both replichores toward the terminus (ter). Several studies have shown that the location of genes relative to ori and ter can have profound effects on regulatory networks and physiological processes. The CtrA phosphorelay is a gene regulatory system conserved in most alphaproteobacteria. It was first discovered in Caulobacter crescentus where it controls replication and division into a stalked and a motile cell in coordination with other factors. The locations of the ctrA gene and targets of this response regulator on the chromosome affect their expression through replication-induced DNA hemi-methylation and specific positioning along a CtrA activity gradient in the dividing cell, respectively. Here we asked to what extent the location of CtrA regulatory network genes might be conserved in the alphaproteobacteria. We determined the locations of the CtrA phosphorelay and associated genes in closed genomes with unambiguously identifiable ori from members of five alphaproteobacterial orders. The location of the phosphorelay genes was the least conserved in the Rhodospirillales followed by the Sphingomonadales. In the Rhizobiales a trend toward certain chromosomal positions could be observed. Compared to the other orders, the CtrA phosphorelay genes were conserved closer to ori in the Caulobacterales. In contrast, the genes were highly conserved closer to ter in the Rhodobacterales. Our data suggest selection pressure results in differential positioning of CtrA phosphorelay and associated genes in alphaproteobacteria, particularly in the orders Rhodobacterales, Caulobacterales and Rhizobiales that is worth deeper investigation.

Learning the distribution of single-cell chromosome conformations in bacteria reveals emergent order across genomic scales

The order and variability of bacterial chromosome organization, contained within the distribution of chromosome conformations, are unclear. Here, we develop a fully data-driven maximum entropy approach to extract single-cell 3D chromosome conformations from Hi-C experiments on the model organism Caulobacter crescentus. The predictive power of our model is validated by independent experiments. We find that on large genomic scales, organizational features are predominantly present along the long cell axis: chromosomal loci exhibit striking long-ranged two-point axial correlations, indicating emergent order. This organization is associated with large genomic clusters we term Super Domains (SuDs), whose existence we support with super-resolution microscopy. On smaller genomic scales, our model reveals chromosome extensions that correlate with transcriptional and loop extrusion activity. Finally, we quantify the information contained in chromosome organization that may guide cellular processes. Our approach can be extended to other species, providing a general strategy to resolve variability in single-cell chromosomal organization.

Vibrionaceae core, shell and cloud genes are non-randomly distributed on Chr 1: An hypothesis that links the genomic location of genes with their intracellular placement

Background

The genome of Vibrionaceae bacteria, which consists of two circular chromosomes, is replicated in a highly ordered fashion. In fast-growing bacteria, multifork replication results in higher gene copy numbers and increased expression of genes located close to the origin of replication of Chr 1 (ori1). This is believed to be a growth optimization strategy to satisfy the high demand of essential growth factors during fast growth. The relationship between ori1-proximate growth-related genes and gene expression during fast growth has been investigated by many researchers. However, it remains unclear which other gene categories that are present close to ori1 and if expression of all ori1-proximate genes is increased during fast growth, or if expression is selectively elevated for certain gene categories.

Results

We calculated the pangenome of all complete genomes from the Vibrionaceae family and mapped the four pangene categories, core, softcore, shell and cloud, to their chromosomal positions. This revealed that core and softcore genes were found heavily biased towards ori1, while shell genes were overrepresented at the opposite part of Chr 1 (i.e., close to ter1). RNA-seq of Aliivibrio salmonicida and Vibrio natriegens showed global gene expression patterns that consistently correlated with chromosomal distance to ori1. Despite a biased gene distribution pattern, all pangene categories contributed to a skewed expression pattern at fast-growing conditions, whereas at slow-growing conditions, softcore, shell and cloud genes were responsible for elevated expression.

Conclusion

The pangene categories were non-randomly organized on Chr 1, with an overrepresentation of core and softcore genes around ori1, and overrepresentation of shell and cloud genes around ter1. Furthermore, we mapped our gene distribution data on to the intracellular positioning of chromatin described for V. cholerae, and found that core/softcore and shell/cloud genes appear enriched at two spatially separated intracellular regions. Based on these observations, we hypothesize that there is a link between the genomic location of genes and their cellular placement.

Computational approaches for inferring 3D conformations of chromatin from chromosome conformation capture data

Chromosome conformation capture (3C) and its variants are powerful experimental techniques for probing intra- and inter-chromosomal interactions within cell nuclei at high resolution and in a high-throughput, quantitative manner. The contact maps derived from such experiments provide an avenue for inferring the 3D spatial organization of the genome. This review provides an overview of the various computational methods developed in the past decade for addressing the very important but challenging problem of deducing the detailed 3D structure or structure population of chromosomal domains, chromosomes, and even entire genomes from 3C contact maps.

Art and Science of the Cellular Mesoscale

Experimental information from microscopy, structural biology, and bioinformatics may be integrated to build structural models of entire cells with molecular detail. This integrative modeling is challenging in several ways: the intrinsic complexity of biology results in models with many closely packed and heterogeneous components; the wealth of available experimental data is scattered among multiple resources and must be gathered, reconciled, and curated; and computational infrastructure is only now gaining the capability of modeling and visualizing systems of this complexity. We present recent efforts to address these challenges, both with artistic approaches to depicting the cellular mesoscale, and development and application of methods to build quantitative models.

A Well-Mixed E. coli Genome: Widespread Contacts Revealed by Tracking Mu Transposition

The three-dimensional structures of chromosomes are increasingly being recognized as playing a major role in cellular regulatory states. The efficiency and promiscuity of phage Mu transposition was exploited to directly measure in vivo interactions between genomic loci in E. coli. Two global organizing principles have emerged: first, the chromosome is well-mixed and uncompartmentalized, with transpositions occurring freely between all measured loci; second, several gene families/regions show "clustering": strong three-dimensional co-localization regardless of linear genomic distance. The activities of the SMC/condensin protein MukB and nucleoid-compacting protein subunit HU-α are essential for the well-mixed state; HU-α is also needed for clustering of 6/7 ribosomal RNA-encoding loci. The data are explained by a model in which the chromosomal structure is driven by dynamic competition between DNA replication and chromosomal relaxation, providing a foundation for determining how region-specific properties contribute to both chromosomal structure and gene regulation.

The Functional 3D Organization of Unicellular Genomes

Genome conformation capture techniques permit a systematic investigation into the functional spatial organization of genomes, including functional aspects like assessing the co-localization of sets of genomic elements. For example, the co-localization of genes targeted by a transcription factor (TF) within a transcription factory. We quantify spatial co-localization using a rigorous statistical model that measures the enrichment of a subset of elements in neighbourhoods inferred from Hi-C data. We also control for co-localization that can be attributed to genomic order. We systematically apply our open-sourced framework, spatial-mHG, to search for spatial co-localization phenomena in multiple unicellular Hi-C datasets with corresponding genomic annotations. Our biological findings shed new light on the functional spatial organization of genomes, including: In C. crescentus, DNA replication genes reside in two genomic clusters that are spatially co-localized. Furthermore, these clusters contain similar gene copies and lay in genomic vicinity to the ori and ter sequences. In S. cerevisae, Ty5 retrotransposon family element spatially co-localize at a spatially adjacent subset of telomeres. In N. crassa, both Proteasome lid subcomplex genes and protein refolding genes jointly spatially co-localize at a shared location. An implementation of our algorithms is available online.

EVR: reconstruction of bacterial chromosome 3D structure models using error-vector resultant algorithm

BACKGROUND

More and more 3C/Hi-C experiments on prokaryotes have been published. However, most of the published modeling tools for chromosome 3D structures are targeting at eukaryotes. How to transform prokaryotic experimental chromosome interaction data into spatial structure models is an important task and in great need.

RESULTS

We have developed a new reconstruction program for bacterial chromosome 3D structure models called EVR that exploits a simple Error-Vector Resultant (EVR) algorithm. This software tool is particularly optimized for the closed-loop structural features of prokaryotic chromosomes. The parallel implementation of the program can utilize the computing power of both multi-core CPUs and GPUs.

CONCLUSIONS

EVR can be used to reconstruct the bacterial 3D chromosome structure based on the contact frequency matrix derived from 3C/Hi-C experimental data quickly and precisely.

Whole-Cell Models and Simulations in Molecular Detail

Comprehensive data about the composition and structure of cellular components have enabled the construction of quantitative whole-cell models. While kinetic network-type models have been established, it is also becoming possible to build physical, molecular-level models of cellular environments. This review outlines challenges in constructing and simulating such models and discusses near- and long-term opportunities for developing physical whole-cell models that can connect molecular structure with biological function.

Transcription of Bacterial Chromatin

Decades of research have probed the interplay between chromatin (genomic DNA associated with proteins and RNAs) and transcription by RNA polymerase (RNAP) in all domains of life. In bacteria, chromatin is compacted into a membrane-free region known as the nucleoid that changes shape and composition depending on the bacterial state. Transcription plays a key role in both shaping the nucleoid and organizing it into domains. At the same time, chromatin impacts transcription by at least five distinct mechanisms: (i) occlusion of RNAP binding; (ii) roadblocking RNAP progression; (iii) constraining DNA topology; (iv) RNA-mediated interactions; and (v) macromolecular demixing and heterogeneity, which may generate phase-separated condensates. These mechanisms are not mutually exclusive and, in combination, mediate gene regulation. Here, we review the current understanding of these mechanisms with a focus on gene silencing by H-NS, transcription coordination by HU, and potential phase separation by Dps. The myriad questions about transcription of bacterial chromatin are increasingly answerable due to methodological advances, enabling a needed paradigm shift in the field of bacterial transcription to focus on regulation of genes in their native state. We can anticipate answers that will define how bacterial chromatin helps coordinate and dynamically regulate gene expression in changing environments.

Sequencing-based methods and resources to study antimicrobial resistance

Antimicrobial resistance extracts high morbidity, mortality and economic costs yearly by rendering bacteria immune to antibiotics. Identifying and understanding antimicrobial resistance are imperative for clinical practice to treat resistant infections and for public health efforts to limit the spread of resistance. Technologies such as next-generation sequencing are expanding our abilities to detect and study antimicrobial resistance. This Review provides a detailed overview of antimicrobial resistance identification and characterization methods, from traditional antimicrobial susceptibility testing to recent deep-learning methods. We focus on sequencing-based resistance discovery and discuss tools and databases used in antimicrobial resistance studies.

From Atoms to Cells: Using Mesoscale Landscapes to Construct Visual Narratives

Modeling and visualization of the cellular mesoscale, bridging the nanometer scale of molecules to the micrometer scale of cells, is being studied by an integrative approach. Data from structural biology, proteomics, and microscopy are combined to simulate the molecular structure of living cells. These cellular landscapes are used as research tools for hypothesis generation and testing, and to present visual narratives of the cellular context of molecular biology for dissemination, education, and outreach.